Diagnostic Report – based on current model outputs (testing 5 countries)
202110gavi-3 – central burden estimates
JHU-Lee Modeling Group
2022-01-12 11:40:12
Table 1. The Model Specs
Specific characteristics of this model are shown in this table.
| Item | Details |
|---|---|
| Disease | Cholera |
| ModelingGroup | JHU-Lee |
| YearRange | 2000-2100 |
| AgeRange | 0-100 |
| CountryList | AFG - AGO - BDI - BEN - BFA - BGD - CAF - CIV - CMR - COD - COG - DZA - ETH - GHA - GIN - GNB - HTI - IND - IRN - IRQ - KEN - LBR - MDG - MLI - MOZ - MRT - MWI - NAM - NER - NGA - NPL - PAK - PHL - RWA - SEN - SLE - SOM - SSD - TCD - TGO - THA - TZA - UGA - YEM - ZAF - ZMB - ZWE |
| SimulatedOutcomes | cohort_size - cases - deaths - dalys |
Figure 1. Coverage Trajectories
The trends of the specific coverage sets for the campaign scenario can be observed in this figure.
Table 2. Coverage Data Check for Campaign Scenario
Age ranges of the different coverage sets include either standard age ranges (as it is the case of Measles) but sometimes it differs by year and country so that several combinations can be possible (See table below).| coverage_set_name | age_from | age_to | freq |
|---|---|---|---|
| cholera-campaign-default | 1 | 100 | 286 |
Figure 2. Fully vaccinated persons (FVPs)
The estimates of fully vaccinated persons (FVPs) are obtained by multiplying coverage from each coverage set and the target population. The following picture shows the Fully Vaccinated Persons (FVPs) at global level by scenario for Cholera.
Table 3. Check the general info
Expected number of rows.| scenario_description | outcome_code | number_of_non_na_rows |
|---|---|---|
| Campaign, Default | cohort_size | 479447 |
| Campaign, Default | cases | 479447 |
| Campaign, Default | deaths | 479447 |
| Campaign, Default | dalys | 479447 |
| No vaccination | cohort_size | 479447 |
| No vaccination | cases | 479447 |
| No vaccination | deaths | 479447 |
| No vaccination | dalys | 479447 |
Figure 3. Missing Value Check
This figure shows the shape of the upload by scenarios and outcomes (whether there are missing values, 1 means no missing value) 
Figure 4. Positive Value Check
This figure shows the pattern of positive values (number of positive values across all simulated countries) 
Figure 5. Check the cohort size – Global
Notion: the interpolated population dataset doesn’t have info for age 100 but has the above, we will leave that out to keep the consistency.
This figure shows the comparison of cohort size against interpolated population in all countries. 
Figure 6. Check the Cohort Size – All Simulated Countries
This figure shows the comparison of cohort size against interpolated population in the simulated countries. 
Table 4. Cohort Size Check in Table Format – All Countries
| Countries | PopulationDifference | Frequency | Proportion |
|---|---|---|---|
| All | 0 | 10100 | 1 |
Table 5. Cohort Size Check in Table Format – Each Country
## `summarise()` has grouped output by 'country'. You can override using the `.groups` argument.| Countries | PopulationDifference | Frequency | Proportion |
|---|---|---|---|
| AFG | 0 | 10100 | 1 |
| AGO | 0 | 10100 | 1 |
| BDI | 0 | 10100 | 1 |
| BEN | 0 | 10100 | 1 |
| BFA | 0 | 10100 | 1 |
| BGD | 0 | 10100 | 1 |
| CAF | 0 | 10100 | 1 |
| CIV | 0 | 10100 | 1 |
| CMR | 0 | 10100 | 1 |
| COD | 0 | 10100 | 1 |
| COG | 0 | 10100 | 1 |
| DZA | 0 | 10100 | 1 |
| ETH | 0 | 10100 | 1 |
| GHA | 0 | 10100 | 1 |
| GIN | 0 | 10100 | 1 |
| GNB | 0 | 10100 | 1 |
| HTI | 0 | 10100 | 1 |
| IND | 0 | 10100 | 1 |
| IRN | 0 | 10100 | 1 |
| IRQ | 0 | 10100 | 1 |
| KEN | 0 | 10100 | 1 |
| LBR | 0 | 10100 | 1 |
| MDG | 0 | 10100 | 1 |
| MLI | 0 | 10100 | 1 |
| MOZ | 0 | 10100 | 1 |
| MRT | 0 | 10100 | 1 |
| MWI | 0 | 10100 | 1 |
| NAM | 0 | 10100 | 1 |
| NER | 0 | 10100 | 1 |
| NGA | 0 | 10100 | 1 |
| NPL | 0 | 10100 | 1 |
| PAK | 0 | 10100 | 1 |
| PHL | 0 | 10100 | 1 |
| RWA | 0 | 10100 | 1 |
| SEN | 0 | 10100 | 1 |
| SLE | 0 | 10100 | 1 |
| SOM | 0 | 10100 | 1 |
| SSD | 0 | 10100 | 1 |
| TCD | 0 | 10100 | 1 |
| TGO | 0 | 10100 | 1 |
| THA | 0 | 10100 | 1 |
| TZA | 0 | 10100 | 1 |
| UGA | 0 | 10100 | 1 |
| YEM | 0 | 10100 | 1 |
| ZAF | 0 | 10100 | 1 |
| ZMB | 0 | 10100 | 1 |
| ZWE | 0 | 10100 | 1 |
Figure 7. Age Distribution for Different Estimates
This figure shows the aggregated (for all countries) age distribution patterns by outcome. 
Figure 8. Global Burden Comparison in 2000-2030.
This figure shows the global (simulated countries) burden values by decades 2000-2030. 
Figure 9. Global Burden Comparison in 2000-2100.
This figure shows the global (simulated countries) burden disease values 2000-2100. 
Figure 10. Case Estimates for Each Country across Scenarios
This figure shows every single simulated countries’ estimated case values and differences 2000-2100. 
Figure 11. Death Estimates for Each Country across Scenarios
This figure shows every single simulated countries’ estimated deaths values and differences 2000-2100. 
Figure 12. Dalys Estimates for Each Country across Scenarios
This figure shows every single simulated countries’ estimated dalys values and differences 2000-2100. 